Multicamera Tracking vs Single Fisheye Camera
Fisheye camera is always worst. Both convolutional networks object detectors and feature-based object detectors rely on the "isometry" of planar image - lack of strong distortions. Multiple camera have added benefit of several independent sources of information - ensembling. If each camera processed by separate network that may help in verification of objects by voting. With very small objects no simple methods would help. Multiple camera may help a little if all camera output processed together (stacked) as single network input, but don't hold much hope - detecting few pixel objects is very difficult, if possible at all.